University Students' Intention to Use Generative AI for English Learning Survey Data

386 valid survey responses from university students collected via convenience sampling. The data was analyzed using structural equation modeling with SmartPLS 4.0 software to examine determinants of AI tool adoption for personalized English learning. The dataset, authored by Li Wang and last updated in May 2026, is shared under a CC-BY-4.0 license.

Use Cases

• Modeling technology acceptance based on performance expectancy, effort expectancy, hedonic motivation, and habit constructs
• Analyzing the mediating role of flow experience on behavioral intention
• Investigating the moderating effect of personal innovativeness on the link between hedonic motivation and intention

Strengths

• 386 valid survey responses provide a substantial sample for analysis
• Analysis was conducted using structural equation modeling, a robust statistical technique
• The dataset is licensed under CC-BY-4.0, allowing for broad reuse

Limitations

• Column-level documentation is absent; field semantics must be inferred after download
• Row count is unknown, which may limit suitability assessment
• Data may reflect bias inherent to convenience sampling from a single population

Provenance

Source

Li Wang

Collection Method

Survey conducted among university students using a convenience sampling method

Freshness

Last updated 2026-05-05 05:29:02